optional: play well with default ordering (e.g. include timestamps)
File structure
.
├── analysis <- all things data analysis
│ └── src <- functions and other source files
├── comm
│ ├── internal-comm <- internal communication such as meeting notes
│ └── journal-comm <- communication with the journal, e.g. peer review
├── data
│ ├── data_clean <- clean version of the data
│ └── data_raw <- raw data (don't touch)
├── dissemination
│ ├── manuscripts
│ ├── posters
│ └── presentations
├── documentation <- documentation, e.g. data management plan
└── misc <- miscellaneous files that don't fit elsewhere
Practice: project management
You have until 11:50 h to work on either …
developing a project structure for your needs from scratch
refactoring/cleaning an existing project1
Optionally: set up version control via git/GitHub for this project.
during the process of manufacturing a ballpoint pen, the cap, the body, the tail, the ink cartridge and the ballpoint are produced separately and unit tested separately.
When two or more units are ready, they are assembled and integration testing is performed, for example a test to check the cap fits on the body.
When the complete pen is integrated, system testing is performed to check it can be used to write like any pen should.
Acceptance testing could be a check to ensure the pen is the colour the customer ordered.
’Literate programming is a methodology that combines a programming language with a documentation language,
thereby making programs more robust, more portable, more easily maintained,
and arguably more fun to write than programs that are written only in a high-level language.
The main idea is to treat a program as a piece of literature, addressed to human beings rather than to a computer.
The program is also viewed as a hypertext document, rather like the World Wide Web. (Indeed, I used the word WEB for this purpose long before CERN grabbed it!)’
To allow the possibility to fully reproduce a scientific study.
To prevent duplicate efforts and speed up scientific progress. Large amounts of research funds and careers of researchers can be wasted by only sharing a small part of research in the form of publications.
To facilitate collaboration and increase the impact and quality of scientific research.
To make results of research openly available as a public good, since research is often publicly funded.
In groups of shared interests and expertise, make a digital poster about challenges and possibilities of working with data in your field of study.
For example, this could tackle issues like collecting, publishing, and sharing data.
Try to make it as concrete and constructive as possible.
You have until 14:20 h to make the poster.
After that, each group will briefly present their poster.
Publishing
How: How can we organise our project from the beginning so that we can publish outputs in the end? Where: Where can I publish my work (platforms, research centers infrastructure, …)?
